Decision support system for lung ventilator settings

ABSTRACT

A ventilator system is capable of displaying complex information patterns in a GUI, thereby allowing a clinician to get subtract complex information from multiple parameters inputs.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. application Ser. No.15/036,553, filed May 13, 2016, which is the U.S. national stage ofPCT/DK2014/050387 filed Nov. 14, 2014, which claims priority of patentapplication DK PA 2013 70690 filed Nov. 15, 2013. The entire content ofeach application is incorporated herein by reference.

FIELD OF THE INVENTION

The present invention relates to a decision support system for lungventilator settings. In particular, the present invention relates to adecision support system for lung ventilator settings, which displaystechnical features of measured physiological parameters providing theclinician with decision support in relation to ventilator settings.

BACKGROUND OF THE INVENTION

Patients residing at the intensive care unit typically receivemechanical support for their ventilation. Selecting the appropriatelevel of mechanical ventilation is not trivial, and it has been shownthat appropriate settings can reduce mortality [1].

A challenge with the settings of a mechanical ventilator is that eachsetting may be beneficial for one physiological parameter of the patientbut negative for another physiological parameter. Currently theclinician may get help by ventilator screens, extra devices monitoringphysiological parameters (capnograph, pulseoximeter, monitor, etc.) andalarm settings if something is wrong.

Clinicians may get stressed by the vast number of settings,physiological parameters, screens, and the relationship between thesevalues and their impact on therapeutic decisions in relation toconflicting goals. Stress and lack of overview can lead to errors, whichcan be fatal in an ICU [2, 3].

Hence, an improved system for minimizing failure in ventilator settingswould be advantageous, and in particular a more efficient and/orreliable system which can minimize stress of the clinician duringventilator setup would be advantageous.

SUMMARY OF THE INVENTION

The present invention relates to a decision support system, whichenables the clinician to get an overview of physiological parameters ofa patient in relation to current and future ventilator settings bypresenting scoring values calculated/determined from physiologicalparameters, respirator settings and clinical preferences. The scoringvalues are displayed for different pairs of scoring values of thepatients, which have conflicting effects in response to over-ventilationand under-ventilation in a graphical user interface (GUI). An example islung trauma vs. acidosis, where acidosis may be compensated for byincreasing ventilation pressure. On the other hand increased ventilationpressure may result in lung trauma. To complicate the case further, thedifferent physiological parameters have different scales and units, anda change in the different physiological parameters (e.g. in response tochanged ventilator settings) therefore reach critical levels ondifferent scales. Overall, these differences make it difficult for theclinician to maintain an overview for all parameters, their relation toclinical preferences and the balancing of these against each othersimply by looking at measured numbers for each parameter. To overcomethis problem the inventors have established different preferencefunctions (CPF) (see FIG. 6 ) for each parameter which translatesrelevant physiological parameters and ventilator settings into a unifiedscale (scoring values). These scoring values simplify the decision phasefor the clinician by having a unified value for when and how actionshould be taken. These functions may be adjusted according to specificpatient information or other requirements. For example, the translationfrom physiological variables and settings to preferences may be furtherimproved by implementing physiological models, which would further allowprediction of patient response to changes in settings and the relationof this response to clinical preferences.

Current aids for setting mechanical ventilation are limited. Measuredphysiological variables are displayed on different devices and aredisplayed individually with the help to clinicians being constituted byalarms on individual values. As such, clinicians are assisted in findingthe variable of priority at present, but not how this is related tooverall physiology or clinical preferences. Experiments have been madewith configural displays, that is, displays where a graphical figuresuch as a face or a physiological analogy to the respiratory system isdisplayed instead of individual numbers. Whilst these may allowclinicians an easier detection of when and how the patient's status ispoor, these attempts have not considered how clinical preferences arerelated to the physiology and current options for setting theventilator. Preference functions, which can convert measured orpredicted physiological variables and ventilator settings into scoringvariables allowing a common scaling across different variables have beenpresented in relation to minimizing risk of barotrauma,acidosis/alkalosis, Oxygen toxicity and absorption atelectasis andhypoxia [5]. However, the scoring variables were presented directly as atable preventing easy and safe interpretation by clinicians.

Thus, an object of the present invention relates to the provision of amechanical ventilation system which solves the above problem of theprior art in relation to displaying patient status information in amanner assisting the clinician in setting/adjusting ventilator settings.

Another object is the provision of integration of physiologicalvariables in a single device and calculation of preference zones, whichgives easy and safe interpretation of the relation between severalphysiological variables and clinical preferences in one graphicaldisplay. A further object is separation of scoring values into twogroups allowing easy detection of the risk of over- andunder-ventilating the patient, which is important in minimising the timeon the ventilator and mortality of the patient. Thus, one aspect of theinvention relates to a mechanical ventilation system for respiration aidof an associated patient, the system being adapted for providingdecision support for choosing a ventilation strategy of said(associated) patient, the system comprising:

-   -   ventilator means capable of mechanical ventilating said        (associated) patient with air and/or one or more medical gases;    -   control means, the ventilator means being controllable by said        control means by operational connection thereto;    -   first measurement means arranged for measuring parameters of the        inspired gas, the first means being capable of delivering first        data to said control means;    -   optionally, second measurement means arranged for measuring the        respiratory feedback of said (associated) patient in expired        gas, the second means being capable of delivering second data to        said control means;    -   third measurement means arranged for measuring one or more blood        values of said (associated) patient, the third means being        capable of delivering third data to said control means,        the control means applying a set of preference functions (CPF)        to convert the first data, the third data, and optionally the        second data, of the (associated) patient into corresponding        scoring values;        the system comprising a graphical user interface (GUI) with a        multi-dimensional coordinate system, wherein at least one pair        of scoring values is arranged for being displayed in the        coordinate system, wherein each pair of scoring values comprises    -   a first scoring value being a translated variable related to        over-ventilation of the (associated) patient, the first scoring        value being displayed at an axis indicative of over-ventilation        in a first direction in the GUI, the first scoring value being        displayed at a distance from a first starting point        corresponding to the first scoring value, and    -   a second scoring value being a translated variable related to        under-ventilation of the (associated) patient, the second        scoring value being displayed at an axis being indicative of        under-ventilation in a second direction in the GUI, the second        scoring value being displayed at a distance from a second        starting point corresponding to the second scoring value.

In the present field a device or system capable of performing mechanicalventilation may also be named an artificial breathing machine, a lifesupport device, or, more popularly, a respirator.

Decision Support:

In the present context the term “decision support” should be understoodin the broadest sense of the term, decision support covers any means forassisting the user, here the clinician, in making the decision. Thisincludes organization, integration and presentation of data as well asproviding suggestions for rational decisions.

Preference Function:

The term “preference function” covers any means for translating a set ofpreferences, here clinical, into mathematical form, e.g. as a functionsuch as an exponential curve, logical rule set etc. Preference functionsare also known as utility theory, and can be presented in the form ofutility or penalty associated with a variable. As used in herepreference functions translates input in the form of ventilator settingsand physiological variables into scoring values annotated e.g. S1, S2, .. . , S6, . . . , Sn. Thus, the term “translate” may, in the context ofthe present application, be understood to mean transforming,(re)calculating, normalizing, etc., as it will readily be appreciated bya skilled person in this field.

Preference Zone:

In the present context, the term preference zone relates to thecalculated graphical display of one or more scoring values calculatedusing preference functions. Preference zones are preferably illustratedtogether for several clinical preferences in one combined illustration,where the graphical display may confer information as to the relationbetween different scoring variables, and the combined display may conferinformation concerning the combined quality of ventilator therapy andstatus of the patient.

Over-Ventilation

In the present context the term “over-ventilation” relates to excessiveventilator support. Excessive ventilation may result in mechanical lungtrauma, alkalosis, ventilator dependency, oxygen toxicity, haemodynamicadverse effects, etc.

Under-Ventilation

In the present context the term “under-ventilation” relates toinsufficient ventilator support. Insufficient ventilation may result inacidosis, stress, low oxygenation, etc.

It may be advantageous to display the scoring values from a commonstarting point in the multi-dimensional coordinate system. Thus, in anembodiment each pair of plotted scoring values has a common startingpoint (e.g. origin ‘O’) in the multi-dimensional coordinate system. FIG.2A shows a specific example of how scoring values can be displayed froma common starting point.

It may also provide better overview for the clinician if scoring valuesindicative of low risk is presented closest to the starting point. Asmentioned above the starting point may be a common starting point forall pairs. Thus, in an embodiment scoring values displayed closer to thestarting point is indicative of lower patient risk than values plottedat greater distance from the starting point. In this context it is to beunderstood that the patient risk relates to the specific physiologicalparameter in question unless otherwise stated. To improve the displayedoverview further, the values for each pair may be displayed in oppositedirections. Thus, in an embodiment the scoring values of a pair aredisplayed in opposite directions. In FIG. 2A the pair S1 and S4 will bedisplayed in opposite directions. Similarly, in FIG. 9 each pair isdisplayed in opposite directions.

Similar, the shape of the multi-dimensional coordinate system may alsoimprove the overview. Thus, in an embodiment the multi-dimensionalcoordinate system has an outer shape being a polygon, each corner in thepolygon and the center (O) of the polygon representing an axis of thescoring values, e.g. S1, . . . , S6, along which the scoring values areplotted. FIGS. 2, 4 and 9 provides example of shapes, which may be usedaccording to the invention depending on the number of pairs. Preferably,each pair comprises two scoring values. Thus, in yet an embodiment thepolygon has an equal number of corners, such as 2-20 corners, such as2-10 corners such as 2-8 corners, such as 4-6 corners, or such as 6corners.

The multi-dimensional coordinate system could also have other shapesthan a polygon, with the maximum value of the scoring value beingpositioned at the circumference of the coordinate system. Thus, in afurther embodiment the multi-dimensional coordinate system is a circleor circular shape (such as an oval), and wherein the circumference ofthe circle or circular shape and the center of the circle (or circularshape) representing an axis of the scoring parameters S1, . . . , S6along which the scoring parameter are plotted/displayed. Examples ofsuch round shapes are also presented in FIG. 4 .

It may be advantageous that the coordinate system comprises two zones,one indicative of scoring parameters representative for over-ventilationand one zone representative for under-ventilation. Thus, in a furtherembodiment the coordinate system is divided by a line through thecenter, dividing the coordinate system into two half's, one halfindicative of over-ventilation of the patient and the second halfindicative of under-ventilation of the patient. It is to be understoodthat such line does not need to be displayed in the GUI. The skilledperson would for example be able to understand that an upper halfrelates to over-ventilation and the lower half relates tounder-ventilation without the line being displayed. FIG. 2A shows suchan example where the dotted line divides the coordinate system into twosuch half's.

The GUI may also display the different pairs of scoring values fromdifferent starting points for each pair. Thus, in an embodiment thestarting point for each pair begins at different points at a line in themulti-dimensional coordinate system dividing the coordinate system intotwo half's, one half indicative of over-ventilation of the patient andthe second half indicative of under-ventilation of the patient. FIG. 9shows examples of such display formats.

The area formed by connecting each plotted/displayed scoring value forma polygon or other shape around the center (also referred to in here as“preference zone) may be indicative of an overall scoring value for thespecific patient with the specific ventilator setting. Thus, in anembodiment the neighbouring displayed scoring values are connected withlines forming an area (or preference zone) in the GUI. In yet anembodiment the GUI presents a value and/or indicator for the areaformed. FIG. 2C shows an example of such area in a coordinate system. InFIG. 9 , examples are displayed where the overall area is the sum ofindividual areas determined for each pair of scoring values. Thus,calculation of the total area provides a total scoring of the currentstatus of the patient and the appropriateness of the mechanicalventilator settings. The same may be the case for an advice or asimulated situation. The system may be adapted for keeping each scoringvalue within certain limits.

In one embodiment the converted scoring values represents patient riskvalues wherein all patient risk values have been normalized to havecomparable patient risk values.

History

It may also be advantageous if the system was capable of displayingscoring values going back in time thereby providing a historic pictureof the calculated scoring values for the patients displayed in an easyconceivable format. Thus, in an embodiment the system is arranged forpresenting an overview over scoring values and/or areas determined atearlier time points. Such historic values may be displayedsimultaneously with current values or as a different setting in the GUI.

By comparing the areas over time information relating to the ventilatorsetting may be determined. Thus, in yet a further embodiment decreasingareas 15 over time, is indicative of improved ventilation parameters andwherein increasing areas over time is indicative of suboptimalventilation parameters.

Modelled/Simulated

By using preference functions, it may be possible to model/simulate howthe patient may respond to changes in ventilator settings. Thus, in yetan embodiment the system is arranged to output scoring values and/orareas in the GUI based on suggested input ventilation parameters by auser.

In yet an embodiment the system using a physiological model (MOD)arranged for generating outcome variables, which, via preferencefunctions, are transformed into modelled/simulated scoring values andmodelled/simulated areas. Examples of physiological models andparameters included in such models, which may be implemented accordingto the present invention are presented in in FIGS. 5-7 and thecorresponding text in the detailed description section.

Advice

It may also be advantageous if the system was able to give decisionsupport in the form of new ventilator settings which would be advisablebased on inputted information on the patients physiological parameters(or scoring values). Again, the system could be arranged forimplementing the described physiological models (MOD). Thus, in yet anembodiment the system is arranged to output an advice for a ventilationstrategy of the patient and display modelled scoring values a polygonzones based on said advice, the system using a physiological model (MOD)to generate said advice. The system may base its advice on a model,which minimizes the area of the polygon zones, without any of thescoring values exceeds predetermined threshold levels. Thus, the systemmay try to minimize the scoring values and thus, also minimize thearea/preference zone in the coordinate system. In yet an embodiment, thecontrol means are adapted for using the first data, optionally, thesecond data and the third data in a physiological model (MOD) of thepatient with physiological variables.

As described above the system is arranged for displaying/plotting one ormore pairs of scoring values in the GUI. In an embodiment, the pairs ofscoring values are selected from the group consisting of:

-   -   mechanical lung trauma vs. acidosis; and/or    -   oxygen toxicity vs. low oxygenation; and/or    -   stress vs. ventilator dependency; and/or    -   Volutrauma vs. atelectrauma and/or    -   Alveolar derecruitment vs. haemodynamic adverse effects of high        ventilator pressure.

Mechanical Lung Trauma:

“Mechanical lung trauma” is to be understood as mechanical damage ormechanical stress to patient organs and the following physiologicaleffects thereof. In the clinic, there is of course a preference foravoiding risk of mechanical lung trauma. Damage may be induced inseveral ways; e.g. damage due to high volumes and/or pressures duringeach breath (often termed volutrauma), damage due to high peak pressurescausing rupture of alveolar and capillary membranes (often termedbarotrauma), damage due to repetitive opening and closing of alveoli(often termed atelectrauma), damage due to spill over of inflammatoryagents (often termed biotrauma), damage of high frequencies such asdynamic hyperinflation due to trapping of gas during expiration andinappropriateness of high frequencies per se (no general term).Clinically measurable variables and ventilator settings for indicatingrisk of mechanical lung trauma include: Inspiratory and expiratorypressure at the different phases of inspiration and expiration such asplateau pressure at end inspiration, set volumes and pressures on theventilator such as tidal volume, inflammatory markers, pressuredifference across the alveolar membrane as for example can be measuredusing a pressure transducer in an esophageal catheter combined withpressure measurements at the mouth.

Management of mechanical ventilation requires the clinician to considerseveral conflicting clinical preferences: pressures or volume settings,for example, should be set so that lung regions are kept open andcollapsed regions are opened (recruited) and gas exchange betweencapillary blood and alveolar gas is secured. However, these settingsshould not be at too high levels where there is increased risk ofcausing mechanical injury to the patient's respiratory system, an effectoften called ventilator-induced lung injury. This is a complex problem,which requires the clinician not only to consider the ventilatorsettings per se, but also other physiological parameters displayed onother devices than the mechanical ventilator. These should be integratedto a physiological and pathophysiological picture of the patient andrelated to the different clinical preferences, and thereafter theclinician tries to predict how the patient will respond to changes inventilator settings and how this response will be related to patientphysiology and clinical preferences.

Acidosis/Alkalosis

In the clinic, there is a preference for avoiding acidosis and alkalosisand the negative associated effects. Clinically measurable variables forindicating acidosis and alkalosis include: values of pH, concentrationof hydrogen ions, concentration of carbon dioxide, concentration ofanions, concentration of cations etc. measured in blood (e.g. arterial,peripheral venous, central venous, mixed venous), calculated valuesindicative of acid base status such as base excess, strong iondifference etc, non-invasive means for indicating acid-base status suchas end-tidal concentration of carbon dioxide and non-invasivemeasurement of tissue and blood carbon dioxide values.

Ventilator Dependency:

In the clinic, there is a preference for minimizing the risk of effectsof prolonged time on mechanical ventilation. These effects includerespiratory muscle atrophy and weakness, work of breathing, ventilatorassociated pneumonia, changes in respiratory drive and immobilisationeffects. Clinically measurable variables for indicating risk ofventilator dependency include: respiratory frequency, minuteventilation, work of breathing, oxygen consumption, carbon dioxideproduction, ventilatory pressures, volumes and flows, pattern ofventilation etc.

Stress:

In the clinic, there is a preference for avoiding stress to thepatient's respiratory muscles, metabolism, cardiac system and mentalstate inappropriately, which can result in worsening patient status.Clinically measurable variables for indicating risk of stressing thepatient include: The rapid shallow breathing index (respiratoryfrequency divided by tidal volume), respiratory frequency, minuteventilation, work of breathing, oxygen consumption, carbon dioxideproduction, ventilatory pressures, volumes and flows, pattern ofventilation, Borg scale and other indications provided by the patient inresponse to questions or detected by the clinician through visualinspection or palpation, etc.

Oxygen Toxicity:

There is a clinical preference for avoiding the negative effects of highlevels of oxygen in the inspiratory gas, these effects including toxiceffects, i.e. cell death due to high levels of oxygen in tissues,absorption atelectasis, i.e. collapse of regions with low ventilation toperfusion ratio, and increased dependency on mechanical ventilation.Clinically measurable variables for indicating risk of oxygen toxicityinclude: level of oxygen in inspired gas and oxygen level in the tissue.

Low Oxygenation:

There is also a clinical preference for avoiding the risk of low levelsof oxygen in blood and tissues of the body. Clinically measurablevariables for indicating risk of low oxygenation include: level ofoxygen in inspired gas, tissue levels of oxygen, saturation, partialpressure and concentration of oxygen in blood (arterial, peripheralvenous, capillary, central and mixed venous), pulse oximetry oxygensaturation, oxygen delivery, tissue oxygen levels etc.

Haemodynamic Adverse Effects:

There is a clinical preference for avoiding the risk of haemodynamicadverse effects of high ventilator pressures and volumes. These effectsinclude reduced cardiac output and hence delivery of oxygen to thetissues, shock, cardiac failure etc. Clinically measurable variables forindicating risk of haemodynamic adverse effects include: ventilatorpressures and volumes such as positive end-expiratory pressure, levelsof pressure in blood (arterial, pulmonary arterial, central venous, andperipheral venous) and calculated variables based on these pressurelevels such as mean arterial pressure (MAP), venous return, cardiacoutput, systemic vascular resistance, heart rate, pulse etc.

Alveolar Derecruitment:

There is clinical preference for avoiding the effects associated withderecruitment of alveoli, i.e. the small air sacs where gas exchangeoccurs in the lungs. Alveolar derecruitment is a common term forcollapse of alveoli, which result in worsening of gas exchange andincrease risk of mechanical trauma to the lung tissue to develop.Prevention of alveolar derecruitment normally encompasses use ofrecruitment manoeuvres to open collapsed alveoli by applying highpressures for short periods of time and use of positive-end expiratorypressure. Clinically measurable variables for indicating risk ofalveolar derecruitment include: ventilator pressures and volumes such aspositive end-expiratory pressure, respiratory system compliance, shapeof the pressure-volume relationship of the respiratory system,functional residual capacity (FRC), levels of extra-vascular lung wateretc.

In a preferred embodiment, the pairs of scoring values are selected fromthe group consisting of:

-   -   mechanical lung trauma vs. acidosis;    -   oxygen toxicity vs. low oxygenation; and/or    -   stress vs. ventilator dependency.

The system may also be arranged for taking into account informationrelating to the specific patient. Thus, in an embodiment, the decisionsupport system is arranged for receiving one or more therapeutic inputparameters relating to the patient, wherein the system is arranged torecalibrate the preference functions (CPF) based on said therapeuticinput parameters, thereby also recalibrate the scoring values generatedby the system. The system may also be adapted for changing the weighingof each preference function based on the therapeutic input parameters.The advantage of using therapeutic input parameters is that the systemcan be adjusted to the specific patient thereby fine-tuning thedisplayed data and improving the decision support. Examples of specifictherapeutic input parameters are information on head trauma (influenceacid/base preferences), age, sex, clinical history, medication, and/orpatient group.

In another aspect, the present invention relates to a computer systemfor cooperating with, and optionally controlling, an (associated)mechanical ventilation system for respiration aid of an associatedpatient, the computer system being adapted for providing decisionsupport for choosing a ventilation strategy of said (associated)patient, the associated mechanical ventilation system comprising:

-   -   ventilator means capable of mechanical ventilating said        (associated) patient with air and/or one or more medical gases;    -   first control means, the ventilator means being connectable to        said first control means by operational connection thereto;    -   first measurement means arranged for measuring parameters of the        inspired gas, the first means being capable of delivering first        data to said first control means;    -   optionally, second measurement means arranged for measuring the        respiratory feedback of said (associated) patient in expired        gas, the second means being capable of delivering second data to        said first control means;    -   third measurement means, arranged for measuring one or more        blood values of said patient, the third means being capable of        delivering third data to said first control means,        the computer system comprising:        second control means applying a set of preference functions to        convert the first data, the third data, and optionally the        second data, of the patient into corresponding scoring values;        and        a graphical user interface (GUI) with a multi-dimensional        coordinate system, wherein at least one pair of scoring values        is arranged for being displayed in the coordinate system,        wherein each pair of scoring values comprises    -   a first scoring value being a physiological variable related to        over-ventilation of the patient, the first scoring value being        displayed at an axis indicative of over-ventilation in a first        direction in the GUI, the first scoring value being displayed at        a distance from a first starting point corresponding to the        first scoring value, and    -   a second scoring value being a physiological variable related to        under-ventilation of the patient, the second scoring value being        displayed at an axis being indicative of under-ventilation in a        second direction in the GUI, the second scoring value being        displayed at a distance from a second starting point        corresponding to the second scoring value.

It is worth mentioning that the invention is particularly advantageousin that the computer system may be implemented independently from amechanical ventilation system by receiving data obtained from such amechanical ventilation system. Thus, by the term “associated” above, itis emphasized that the mechanical ventilation system does not form partof the computer system. Thus, the first control means of the mechanicalventilation system and the second control means of the computer systemmay be separate entities, or they may form a single entity. The data maybe received directly and/or continuously, or the data can be receivedfrom a storage entity at discrete times, regularly or upon choice of auser. Thus, the computer system according to the invention may beapplied both for continuous surveillance and decision support of apatient and/or for analysis of earlier data, e.g. obtained from apatient file with the appropriate data therefore.

Colouring of Lines/Areas

The information in the GUI may be further expanded by also using colourcodes or colour scaling. Thus, in an embodiment the colouring of linesand/or areas are indicative of the total patient risk. For example if anarea is e.g. green the total penalty is low, if an area is yellow thepenalty is medium and if the colour is red the total penalty is high.

In another embodiment, the colouring of lines and/or areas areindicative of extra patient risk in addition to risks presented on theaxes. For example, if the whole area is coloured red a risk of “adversehaemodynamic effects” is detected.

In another aspect, the invention relates to a computer program productbeing adapted to enable a computer system comprising at least onecomputer having data storage means in connection therewith to controlmechanical ventilation system for respiration aid of an associatedpatient according to the invention.

This aspect of the invention is particularly, but not exclusively,advantageous in that the present invention may be accomplished by acomputer program product enabling a computer system to carry out theoperations of the mechanical ventilation system for respiration aid ofan associated patient of the invention when down- or uploaded into thecomputer system. Such a computer program product may be provided on anykind of computer readable medium, or through a network. Thus, it iscontemplated that the invention may be implemented by uploaded andexecuting a computer program product on a computer system adapted forcooperating with, and optionally controlling, an already existingmechanical ventilation system.

The individual aspects of the present invention may each be combinedwith any of the other aspects. These and other aspects of the inventionwill be apparent from the following description with reference to thedescribed embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

The method according to the invention will now be described in moredetail with regard to the accompanying figures. The figures show one wayof implementing the present invention and is not to be construed asbeing limiting to other possible embodiments falling within the scope ofthe attached claim set.

FIG. 1 is a schematic drawing of a mechanical ventilation systemaccording to the present invention.

FIG. 2 shows a preferred output format in the GUI in a schematic format.

FIG. 3 shows a screenshot of a preferred output format in the GUI.

FIG. 4 shows examples of output formats in the GUI.

FIG. 5 shows the structure of a decision support system according to theinvention, illustrating the components of the system (ovals) and thefunctionality (dashed lines).

FIG. 6 shows examples of preference functions (CPF) where physiologicalvariables and ventilator settings are translated into a unified scale(scoring values).

FIG. 7 illustrates a set of mathematical model components of a decisionsupport system (DSS) including the mathematical representation of aphysiological model of respiratory control.

FIG. 8 is a schematic flow chart of a method according to the invention.

FIG. 9 shows examples of output formats in the GUI with each pair beingdisplayed on a line. The areas of the columns and the areas under thegraph represent single preference zones (areas) for each pair. The sumof these individual preference zones represents the overall preferencezone for the specific patient.

The present invention will now be described in more detail in thefollowing.

DETAILED DESCRIPTION OF THE INVENTION

As described above, the core aspect of the invention is the use ofpreference functions to calculate scoring values and correspondingpreference zones/areas 15 from clinically measured variables allowingintegration of relevant mechanical ventilation variables for a patientinto a single presentation covering the contrasting preferences relatedto mechanical ventilation helping the clinician to minimise risk ofover-ventilating and under-ventilating the patient.

FIG. 1 is a schematic drawing of a mechanical ventilation system 10 forrespiration aid of an associated patient 5, P, the system being adaptedfor displaying/plotting information of physiological parameters in amanner providing the clinician with information which is difficult tosubtract from mere number values. The respiration aid may be fullycontrolled or supported.

The system comprises ventilator means 11, VENT capable of mechanicalventilating said patient with air and/or one or more medical gases, e.g.oxygen and/or nitrogen. Conventional ventilator systems currentlyavailable may be modified or adapted for working in the context of thepresent invention.

Furthermore, control means 12, CON is comprised in the system 10, theventilator means 11 being controllable by said control means 12 byoperational connection thereto, e.g. appropriate wirings and interfacesas it will be appreciated by the skilled person working with mechanicalventilation.

Additionally, measurement means 11 b, M_G2 are arranged for measuringthe respiratory feedback of said patient in the expired gas 6 b inresponse to the mechanical ventilation, e.g. respiratory frequency orfraction of expired carbon dioxide commonly abbreviated FECO₂, cf. thelist of some well-known abbreviations below. The measurement means areshown as forming part of the ventilator means 11, but couldalternatively form an independent entity with respect to the ventilatormeans without significantly change the basic principle of the presentinvention. Similarly, the computer system according to the invention maywork independently from a mechanical ventilator.

Additionally, measurement means 11 b, M_G2 are arranged for measuringparameters of the inspired gas 6 a, the first means being capable ofdelivering first data D1 to said control means. It should be noted thatthe first data D1 may also include the ventilator settings (Vt_SET).

The measurement means M_G (1 and 2) are capable of delivering the firstdata D1 and the second data D2 to the control means 12 CON byappropriate connection, by wire, wirelessly or by other suitably dataconnection.

The control means 12 CON is also capable of operating the ventilationmeans by providing ventilatory assistance so that said patient 5 P is atleast partly breathing spontaneously, and, when providing suchventilatory assistance, the control means being capable of changing one,or more, volume and/or pressure parameters Vt_SET of the ventilatormeans so as to detect changes in the respiratory feedback in general ofthe patient by the measurement means M_G (1 and 2).

The control means is further being arranged for receiving third data D3,preferably obtainable from blood analysis of said patient performed byblood measurement means M_B 20, the third data being indicative of therespiratory feedback in the blood of said patient, e.g. pHa, PACO2, PA02etc. Notice that the blood measurement means M_B 20 is not necessarilycomprised in the ventilator system 10 according to the presentinvention. Rather, the system 10 is adapted for receiving second data D2from such an entity or device as schematically indicated by theconnecting arrow. It is however contemplated that a blood measurementmeans M_B could be comprised in the system 10 and integrated therein. Inthis embodiment, the mechanical ventilator system comprises at least theventilator means VENT 11, the measurement means M_G (1 and 2) 11 (a andb), and the control means CON 12. The physiological model MOD isimplemented on the control means, e.g. in an appropriate computingentity or device.

In one variant of the invention, the third data D3 could be estimated orguessed values being indicative of the respiratory feedback in the bloodof said patient, preferably based on the medical history and/or presentcondition of the said patient. Thus, values from previously (earliersame day or previous days) could form the basis of such estimated guessfor third data D3.

The control means is adapted for using both the first data D1 indicativeof parameters of the inspired gas, the second data D2 indicative ofchanges of respiratory feedback in expired air 6 b, and the third dataD3 indicative of the respiratory feedback in the blood 7. By the use ofpreference functions the system translates D1, D2 and D3 into scoringvalues displayed in a coordinate system 14 in a graphical user interface(GUI) 13.

The principle of this invention is further exemplified in FIGS. 2 and 3.

FIG. 2A illustrates an example of a multidimensional coordinate system14, in here displayed as a hexagon, with the scoring values S1-S6 beingdisplayed at an axis from the center, or origin, O towards each cornerof the hexagon. The scoring values being displayed in the upper half 14a is indicative of over-ventilation of the patient, whereas the scoringvalues being displayed in the lower half 14 b is indicative ofunder-ventilation.

It is to be understood that scoring values representative for currentstatus S1, modelled/simulated status S1′ (based on user input) andadvice S1″ based on a physiological model implemented in the system mayall be displayed. The three different values may be displayedsimultaneously or by selection of the user. The same can be the case forother scoring values.

FIG. 2B shows an example of a coordinate system shaped as a square. Suchsquare will then only display two scoring pairs, S1 vs. S4, and S2 vs.S3, respectively. FIG. 2C shows a circular coordinate system, where thescoring values are displayed on an axis going from the center towards apoint on the circumference of the circle. In FIG. 2C, an area 15constituted by the displayed scoring values is also displayed. Such anarea may be indicative of the overall quality of the ventilatorsettings. Again such areas may be displayed for current status,modelled/simulated status (based on user input) and advice based on aphysiological model implemented in the system. Thus, the system applythe physiological model (MOD) to generate said advice basing its adviceon a model which minimizes the area of the polygon zones, without any ofthe scoring values exceeds predetermined threshold levels. Thus, thesystem may try to minimize the scoring values and thus also minimize thearea/preference zone in the coordinate system.

FIG. 3 is an actual screenshot of how data may be presented on amonitor, with actual scoring values presented. Areas 15 are alsopresented. To the right, the multi-dimensional coordinate system 14 isshown, i.e. a hexagon, the upwards direction in the figure being thedirection representing over-ventilation OV and the downwardsrepresenting under-ventilation UV as in FIG. 2 . To the left in FIG. 3 ,the current values, and simulated values of the respiratory volume in asingle breath Vt and the fraction of inhaled oxygen FiO₂, respectively,are shown. Additionally, the ‘Advice’ according to the present isdisplayed next to the simulated values.

FIG. 4 shows other shapes (pentagon 141, octagon 142, heptagon 143,decagon 144, non-polygon 145) which may be implemented in a systemaccording to the invention. The number of corners in the polygon maydepend on the number of scoring pairs included in the system. Noticethat for a polygons with an uneven number of corners, e.g. a pentagon,there will be one or more pairs of scorings values displayed, but atleast one scoring value will be unpaired. Thus, in the pentagon shownone scoring value, e.g. S5, may be unpaired.

FIG. 5 illustrates the conceptual model behind the system according tothe invention. The core of the system is a set of physiological modelsdescribing pulmonary gas exchange, acid-base chemistry, lung mechanicsetc. the system tunes these models to the individual patient such thatthey describe accurately current measurements, labelled “OutcomeVariables” in the figure.

The ovals illustrates components of the system, which includes

-   -   ventilator settings (f, Vt, FiO2, LE-ratio, PEEP and PIP);    -   model parameters (shunt, fA2, Vd, compliance, DPG, Hb, COHb,        MetHb, temp, Q, VO2 and VCO2);    -   physiological models and their variables (FetCO2, FetO2, SaO2,        PaO2, PaCO2, pHa, SvO2, PvO2, PvCO2, and pHv);    -   those variables selected as surrogate outcomes (PIP, SvO2, SaO2,        pHv and FiO2); and    -   functions describing clinical preference (barotrauma, hypoxia,        acidosis-alkalosis, oxygen toxicity).

Once tuned, the models are used by the system to simulate the effects ofchanging ventilator settings. These simulations are then used with a setof “Clinical preference functions” (CPF). Some of these functions areillustrated in FIG. 6 and describe clinical opinion as to the outcomevariables. For example, an increased inspiratory volume will reduce anacidosis of the blood while detrimentally increasing lung pressure.Appropriate ventilator settings Vt_SET therefore imply a balance betweenthe preferred value of pH weighted against the preferred value of lungpressure. A number of these balances exist, and the clinical preferencefunctions quantitatively weight these, calculating a total score for thepatient for any possible ventilation strategy. As the individualpreference scores all range between 0 and 0.5 and the patients totalscore is a sum of these, then the patients score can range between 0 and2, with 0 being the best condition and 2 the worst condition. The modelsimulations and preference functions are then used together in a processcalled “optimization” where the ventilator settings resulting insimulations giving the preferred patient score, i.e. the lowest, arefound. These are then said to be the optimal ventilator settings and area target advice. If the target advice is a substantial distance fromcurrent ventilator settings then “advice steps” may be generated, thesesteps represent a clinically reasonable step toward the target advicewithout overly aggressive modifications in ventilator settings.

FIG. 7 illustrates the set of mathematical model components of adecision support system (DSS) including the mathematical representationin the form of physiological model of respiratory control that may beapplied in the context of the present invention.

The DSS includes models of: pulmonary gas exchange (A); acid-base statusand oxygenation of blood (B); acid-base status of CSF (C); cardiacoutput, and arterial and mixed venous pools (D); interstitial fluid andtissue buffering, and metabolism (E); and chemoreflex model ofrespiratory control (F).

FIG. 7A illustrates the structure of the model of ventilation andpulmonary gas exchange. FIG. 7B illustrates the structure of the modelof oxygenation and acid-base status in the blood. FIG. 7C illustratesDuffin's model of CSF with appropriate model constants [3, 4]. Thismodel includes mass-action equations describing water, phosphate andalbumin dissociation plus the formation of bicarbonate and carbonate,and an equation representing electrical neutrality (equations 101-106).In addition, equation (107) is used to describe the equilibration ofPCO₂ with arterial blood across the blood-brain barrier. Equation (108)is a modification to Duffin's model which allows calibration of the CSFto conditions where blood bicarbonate, and hence buffer base (BB) orstrong ion difference (SID) are modified, such as metabolic acidosiswhere blood bicarbonate is reduced, or chronic lung disease where bloodbicarbonate is increased.

The model illustrated in FIG. 7 includes compartments representing CO₂transport and storage including the arterial and venous compartments,and circulation represented as cardiac output (Q) (FIG. 7D).

FIG. 7E illustrates the model of interstitial fluid and tissuebuffering, and metabolism included in the system. This includes oxygenconsumption (VO₂) and carbon dioxide production (VCO₂).

FIG. 7F illustrates the model of respiratory control of Duffin, i.e.equations 109-112. Alveolar ventilation is modeled as a peripheral andcentral chemoreflex response to arterial and cerebrospinal fluid (CSF)hydrogen ion concentration ([H⁺ _(a)] and [H⁺ _(csf)]) plus wakefulnessdrive. Equation (109) describes the peripheral drive (Dp) as a linearfunction of the difference between [H⁺ _(a)] and the peripheralthreshold (Tp). The slope of this function (Sp) represents thesensitivity of the peripheral chemoreceptors.

Equation (111) describes central drive (Dc) as a linear function of thedifference between [H⁺ _(csf)] and the central threshold (Tc). The slopeof this function (Sc) represents the sensitivity of centralchemoreceptors. Equation (112) describes the alveolar ventilation as thesum of the two chemoreflex drives and the wakefulness drive (Dw).Equation (113) describes the minute ventilation as alveolar ventilationplus ventilation of the dead space, that is equal to the product oftidal volume (Vt) and respiratory frequency (f).

The model described above can be used to simulate respiratory control.The model enables simulation of the control of alveolar ventilationtaking into account pulmonary gas exchange, blood and CSF acid-basestatus, circulation, tissue and interstitial buffering, and metabolism.

FIG. 8 is a schematic flow chart of a method according to the invention.The invention thus relates to a method for operating a mechanicalventilation system for respiration aid of an associated patient 5, P,the system being adapted for providing decision support for choosing aventilation strategy of said patient, the method comprising:

-   -   Step 1 providing ventilator means 11, VENT capable of mechanical        ventilating said patient with air and/or one or more medical        gases;    -   Step 2 providing control means 12, CON, the ventilator means        being controllable by said control means by operational        connection thereto Vt_SET;    -   Step 3 providing first measurement means 11 a, M_G1 arranged for        measuring parameters of the inspired gas 6 a, the first means        being capable of delivering first data D1 to said control means;        optionally, second measurement means 11 b, M_G2 arranged for        measuring the respiratory feedback of said patient in expired        gas 6 b, the second means being capable of delivering second        data D2 to said control means;    -   Step 4 providing third measurement means 20, M_B, arranged for        measuring one or more blood values of said patient, the third        means being capable of delivering third data D3 to said control        means, the control means applying a set of preference functions        CPF to convert the first data D1, the third data D3, and        optionally the second data D2, of the patient into corresponding        scoring values, S1, . . . , S6;    -   the system comprising a graphical user interface (GUI) 13 with a        multi-dimensional coordinate system 14, wherein at least one        pair of scoring values is arranged for being displayed in the        coordinate system, wherein each pair of scoring values providing    -   Step 5 a first scoring value, S1, S2, and S6, being a translated        variable related to over-ventilation of the patient, the first        scoring value being displayed at an axis indicative of        over-ventilation in a first direction OV in the GUI, the first        scoring value being displayed at a distance from a first        starting point O corresponding to the first scoring value, and    -   Step 6 a second scoring value, S3, S4, and S5, being a        translated variable related to under-ventilation of the patient,        the second scoring value being displayed at an axis being        indicative of under-ventilation in a second direction UV in the        GUI, the second scoring value being displayed at a distance from        a second starting point O corresponding to the second scoring        value.

FIG. 9 is illustrations showing alternative ways of displaying thescoring values in the GUI where the values indicative ofover-ventilation and under-ventilation are presented on a commonhorizontal, or vertical axis. Notice that the pairs of scoring values,S1 vs. S4, etc., are then represented at separate centers O1, O2, O3,and O4, in the coordinate system of example A. Similarly, in thecoordinate system of examples B, C and D, there are separate centers forthe pairs of scoring values. The axis (indicated by the dotted lines inexamples A, B, C and D) divides the scoring values into valuesrepresentative of over- and under-ventilation. It should be noted thatembodiments and features described in the context of one of the aspectsof the present invention also apply to the other aspects of theinvention.

All patent and non-patent references cited in the present application,are hereby incorporated by reference in their entirety.

Glossary

-   CSF Cerebral spinal fluid-   Vt Respiratory volume in a single breath, tidal volume-   Vt_SET Respiratory volume settings for mechanical ventilation, tidal    volume-   FECO₂ Fraction of carbon dioxide in expired gas.-   FE′CO₂ Fraction of carbon dioxide in expired gas at the end of    expiration.-   PECO₂ Partial pressure of carbon dioxide in expired gas.-   PE′CO₂ Partial pressure of carbon dioxide in expired gas at the end    of expiration.-   RR respiratory frequency (RR) or, equivalently, duration of breath    (including duration of inspiratory or expiratory phase)-   pHa Arterial blood pH-   PaCO2 Pressure of carbon dioxide level,-   SaO2 Oxygen saturation of arterial blood-   PpO2 Pressure of oxygen in arterial blood

REFERENCES

-   1. The Acute Respiratory Distress Syndrome (ARDS) Network (2000)    Ventilation with lower tidal volumes as compared with traditional    tidal volumes for acute lung injury and the acute respiratory    distress syndrome. N Engl. J Med. 342:1301-1308.-   2. Arnstein F. (1997) Catalogue of human error. Br J Anaesth.    79:645-656.-   3. Wysocki M, Brunner J X. (2007). Closed-Loop Ventilation: An    emerging standard of care? Crit Care Clin. 23:223-240.-   4. Arnstein F. (1997) Catalogue of human error. Br J Anaesth.    79:645-656.-   5. Allerød C, Rees S E, Rasmussen B S, Karbing D S, Kjægaard S,    Thorgaard P, Andreassen S. (2008). A decision support system for    suggesting ventilator settings: Retrospective evaluation in cardiac    surgery patients ventilated in the ICU. Comput Meth Prog Biomed.    92:205-212.

1.-25. (canceled)
 26. A method for mechanical ventilation forrespiration aid of an associated patient, the method comprising:mechanically ventilating a patient with medical gases; during themechanical ventilation: receiving first data indicative of parameters ofinspired gas of said associated patient; receiving second dataindicative of a respiratory feedback of said associated patient inexpired gas; applying a set of preference functions to convert the firstdata and the second data into corresponding scoring values; anddisplaying, on a graphical user interface (GUI), multiple pairs of thescoring values are displayed in a multi-dimensional coordinate system,wherein each pair of scoring values comprises a first scoring value anda second scoring value, the first and second scoring values havingconflicting effects in response to over-ventilation andunder-ventilation in the graphical user interface, wherein: the firstscoring value is a translated variable related to the over-ventilationof the associated patient, the first scoring value being displayed at afirst axis indicative of the over-ventilation in a first direction inthe GUI, the first scoring value being displayed at a first distancefrom a first starting point corresponding to the first scoring value,and the second scoring value is a translated variable related to theunder-ventilation of the associated patient, the second scoring valuebeing displayed at a second axis indicative of the under-ventilation ina second direction in the GUI, the second scoring value being displayedat a second distance from a second starting point corresponding to thesecond scoring value, wherein the first scoring value and the secondscoring value in each pair of scoring values represent opposite clinicalpreferences, and different pairs of scoring values represent clinicalpreferences associated with different physiological variables.
 27. Themethod of claim 26, further comprising: receiving third data indicativeof one or more blood values of said associated patient; and applying theset of preference functions to convert the first data and the seconddata into scoring values.
 28. The method of claim 26, wherein each pairof plotted scoring values have a common starting point in themulti-dimensional coordinate system, wherein the first starting pointand the second starting point are the common starting point.
 29. Themethod of claim 26, wherein the first and second scoring valuesdisplayed closer to the first and second starting points, respectively,are indicative of lower associated patient risk than values plotted atgreater distance from the first and second starting points,respectively.
 30. The method of claim 26, wherein the first and secondscoring values of each pair are displayed in opposite directions. 31.The method of claim 26, wherein the multi-dimensional coordinate systemhas an outer shape being a polygon, each corner in the polygon and thecenter of the polygon representing a scoring axis of the scoring values,along which scoring axis the scoring values are plotted.
 32. The methodof claim 26, wherein the multi-dimensional coordinate system is a circleor circular shape, and wherein the first and second scoring values areplotted or displayed along a circle axis between a circumference of thecircle or circular shape and a center of the circle or circular shape.33. The method of claim 26, wherein the first and second scoring valueshave the conflicting effects with respect to: mechanical lung trauma vs.acidosis; oxygen toxicity vs. low oxygenation; stress vs. ventilatordependency; volutrauma vs. atelectrauma and/or alveolar derecruitmentvs. adverse heamodynamic effects of high ventilator pressure.
 34. Themethod of claim 26, wherein the first and second scoring values have theconflicting effects with respect to: mechanical lung trauma vs.acidosis; oxygen toxicity vs. low oxygenation; and/or stress vs.ventilator dependency.
 35. The method of claim 26, further comprising:receiving one or more therapeutic input parameters relating to theassociated patient; and recalibrating the preference functions based onsaid therapeutic input parameters, thereby recalibrating the scoringvalues generated by the system.
 36. The method of claim 35, furthercomprising changing a weight of each preference function based on thetherapeutic input parameters.